Welding tendency for selected contact materials under different switching conditions

Książkiewicz, Andrzej; Janiszewski, J.

doi:10.17531/ein.2019.2.7

Cited by 9 publications

(7 citation statements)

References 17 publications

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“…As AgNi and AgCdO are less resistant to contact welding, the phenomenon occurred in them and the contact made of AgSnO 2 and AgSnO 2 P remained resistant. Studies have shown [25] that contact welding occurs only when the switching phase is π/2 and a bounce occurs. However, some materials, like AgSnO 2 and AgSnO 2 P, are immune to contact welding at this current level, as compared to AgNi and AgCdO.…”

Section: Resultsmentioning

confidence: 99%

Change in Electric Contact Resistance of Low-Voltage Relays Affected by Fault Current

2019

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Contact resistance is an important maintenance parameter for electromagnetic switches, including low-voltage relays. The flow of significant current through electric contacts may influence the contact surface and thus the value of the electric contact resistance (ECR). The change in ECR is influenced not only by the value of current but also by the current phase. Therefore, the impact of the switching short-circuit current’s phase on the ECR was analyzed in this paper. Significant changes in the resistance after each switching cycle were observed. The ECR decreased significantly after each make operation, and a correlation with current amplitude, total let-through energy, and short-circuit time was not observed.

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Section: Resultsmentioning

confidence: 99%

Change in Electric Contact Resistance of Low-Voltage Relays Affected by Fault Current

2019

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“…Relevant to the welding strength is the load current and the duration of the bounce. The strength of the weld increases with the amplitude of the applied current [4]. As bouncing events become shorter with each subsequent bounce an increase in the weld strength for late bounce events, somewhat growing exponentially past the 4 th bounce can be observed [75].…”

Section: ) Contact Weldingmentioning

confidence: 99%

“…The EMR is a versatile component found in many electrical systems e.g., consumer products or safety critical applications in the nuclear-or aviation industry. Over several decades, EMR failure modes and mechanisms in particular relating to electrical contact degradation have been subject of extensive studies [1], in order to improve design and material properties [2]- [4].…”

Section: Introductionmentioning

confidence: 99%

Prognostics for Electromagnetic Relays Using Deep Learning

et al. 2022

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Electromagnetic Relays (Electromagnetic Relay (EMR)s) are omnipresent in electrical systems, ranging from mass-produced consumer products to highly specialised, safety-critical industrial systems. Our detailed literature review focused on EMR reliability highlighting the methods used to estimate the State of Health or the Remaining Useful Life emphasises the limited analysis and understanding of expressive EMR degradation indicators, as well as accessibility and use of EMR life cycle data sets. Prioritising these open challenges, a deep learning pipeline is presented in a prognostic context termed Electromagnetic Relay Useful Actuation Pipeline (EMRUA). Leveraging the attributes of causal convolution, a Temporal Convolutional Network (TCN) based architecture integrates an arbitrary long sequence of multiple features to produce a remaining useful switching actuations forecast. These features are extracted from raw, high volume life cycle data sets, namely EMR switching data (Contact-Voltage, Contact-Current). Monte-Carlo Dropout is utilised to estimate uncertainty during inference. The TCN hyperparameter space, as well as various methods to select and analyse long sequences of multivariate time series data are investigated. Subsequently, our results demonstrate improvements using the developed statistical feature-set over traditional, time-based features, commonly found in literature. EMRUA achieves an average forecasting mean absolute percentage error of ±12 % over the course of the entire EMR life. INDEX TERMSElectromagnetic relay, prognostics, prognostics and health management, predictive maintenance, remaining useful life, artificial intelligence, deep learning, temporal convolutional networks, Monte-Carlo dropout. ABBREVIATIONS AT Arcing time. BT Bounce time. CAE Convolutional auto encoder. CC Coil current. CI Contact current. CNN Convolutional neural network. CR Contact resistance. CT Closing time. CV Contact voltage. DCR Dynamic contact resistance. DI Degradation indicator. EI Exponential indexing. The associate editor coordinating the review of this manuscript and approving it for publication was Sajid Ali . EMR Electromagnetic relay. EMRUA Electromagnetic relay useful actuation pipeline. EOL End of life. FC Fully connected layer. GI Growing-sequence indexing. LI Linear indexing. LSTM Long-short-term-memory network. MAE Mean absolute error. MAPE Mean absolute percentage error. MCD Monte-carlo dropout. MVTD Multivariate time series data. NN Neural network. OT Over-travel time.

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“…In electromagnetic relays, the flow of current of a considerable value can lead to the emergence of an electrodynamic force, affecting the contact system, and it can be large enough to cause a dynamic opening of the contacts. As a result, an electric arc will occur between the contacts, which may be welded [1][2][3][4] when the contacts close again. Welded contact will make the relay inoperable, which will necessitate its replacement or an exchange of the entire device within which it is incorporated.…”

Section: Introductionmentioning

confidence: 99%

“…There are studies that utilize the contact force to describe the working principles of electrical equipment [16]. Many studies combine electrodynamic bounce of contacts with contact welding [1][2][3]. As shown in these studies there is a relation between contact bounce, contact welding, and electrodynamic force, however they do not focus on that subject.…”

Section: Introductionmentioning

confidence: 99%

Electrodynamic Contact Bounce Induced by Fault Current in Low-Voltage Relays

et al. 2019

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Due to fault currents occurring in electrical installations, high electromagnetic force values may be induced in current paths of low-voltage electromagnetic relays. This force may lead to an electromagnetic bounce that will further result in an electric arc ignition between contacts, and under some circumstances, it will result in contact welding. For the proper exploitation of relays, the threshold value of the maximum current, and thus the electrodynamic force, should be known. This force depends on several factors, including: contact materials, dimensions of relay current paths, relay electromagnetic coil, etc. This paper presents the results of calculations and an experiment on electromagnetic forces, which cover these factors. A static closing force, acting on the contacts, and the fault current were measured. As a result, values of the force and current threshold were obtained, which inform when an electrodynamic bounce may occur. The obtained result may be used in designing contact rivets and relay current paths together with the selection of adequate fault protection devices.

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Welding tendency for selected contact materials under different switching conditions

Cited by 9 publications

References 17 publications

Change in Electric Contact Resistance of Low-Voltage Relays Affected by Fault Current

Change in Electric Contact Resistance of Low-Voltage Relays Affected by Fault Current

Prognostics for Electromagnetic Relays Using Deep Learning

Electrodynamic Contact Bounce Induced by Fault Current in Low-Voltage Relays

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